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Foth Infrastructure & Environment, LLC

Mobile LiDAR & sUAS Case Study

Project Summary

Project
The Hubbel Avenue Corridor in Des Moines, Iowa currently serves over 23,000 vehicles per day and has a crash rate that is five times greater than the Iowa statewide crash rate. To reduce the high number of traffic accidents on this corridor, the City of Des Moines Engineering Department decided it needed to reconstruct approximately one mile of the roadway to improve safety. The department contracted Foth Infrastructure & Environment to perform engineering, design services, and collect survey data to build a digital terrain model of the existing ground conditions. The project team faced several challenges, including how to effectively collect aerial imagery and create a digital terrain model of the existing ground conditions. To achieve desired accuracy while ensuring safety of survey personnel, the geospatial team chose a unique combination of aerial-based LiDAR using a small unmanned aircraft system (sUAS) and ground-based mobile scanning to collect the data, and used reality modeling to produce near real-time site conditions, enabling the design team to make more informed decisions.

Solution
After considering site accessibility and safety, project extents, the accuracy of the deliverable, budget, and schedule the geospatial team at Foth concluded that a combination of aerial-based LiDAR using a sUAS and ground-based mobile scanning would achieve the desired results and satisfy all concerns. These methods would drastically reduce safety concerns by limiting field time and producing a high accuracy point cloud on the roadway and within the right-of-way. These images were used to extract a point cloud for the entire project site, and the team used ContextCapture to create a 3D reality mesh of the area. MicroStation served as an engine on which the TopoDOT software ran. TopoDOT was used to interpolate cross sections and create breaklines from the point clouds. GEOPAK with OpenRoads technology was used to bring all post-processed breaklines and filtered point clouds together into a single digital terrain model (DTM), and the final DTM from OpenRoads was the main deliverable to the design team.

Outcome
The team only required three days of field time versus 15 days had conventional methods been used. The only time field staff were on foot near traffic was to set control points. The team used a fixed wing drone to fly over the project at low altitudes to supplement the mobile LiDAR data with over 1,000 images during its 27-minute flight. The quality of the final color orthomosaic exceeded the design team’s expectations and the accuracy of the result was a huge benefit to the designers. The team could reduce field time by over two weeks, replacing it with only a handful of days in the office performing post-processing and mapping functions. The cost savings were passed on to the client, and the client received higher quality deliverables. The team reduced field time by over two weeks, replacing it with only a few days, performing post-processing and mapping functions, optimizing safety, and minimizing costs while producing a quality deliverable that exceeded client expectations.

Software
Bentley’s reality modeling applications provided the technology necessary for merging the data captured from two different collection sources into a geo-referenced, manageable model. Using Descartes, the team classified and refined the point clouds, and with ContextCapture processed the point clouds and more than 1,000 images into a 3D reality mesh. OpenRoads provided the final deliverable to the design team, bringing all the information into a single digital terrain model.